The three major types of systems widely being employed in fixed and mobile communication systems are Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA) and Code Division Multiple Access (CDMA).
The oldest system, FDMA, divides the available frequency spectrum into several channels, and allocates channels to users as needed. As a result, the number of channels in an FDMA system is limited directly by the available bandwidth.
In TDMA, each user transmits over the same frequency, but the channel is divided into time slots, so that each user only transmits a portion of information at the allotted time.
While FDMA and TDMA systems keep the users from transmitting either on the same frequency or at the same time, CDMA allows all users to transmit over the same broadband frequency at the same time. In both the time domain and the frequency domain, CDMA signals appear to be on top of each other. However, before transmission, each user's signal is modulated by a unique spreading code, which increases the signal bandwidth substantially more than otherwise required for transmitting the baseband signal. At the receiver, the spreading code then is applied to the received signal to extract the desired data.
CDMA spread spectrum modulation has been proposed for several mobile terrestrial and/or satellite networks. It has been especially recommended, implemented, and field tested for cellular terrestrial systems. While it has been shown that CDMA, under special channel conditions, potentially can achieve a high bandwidth efficiency, its performance substantially and considerably degrades if the power levels of system users are not equal or approximately equal. Interference from high powered signals degrades the performance of faded signals. This effect is known as the near-far problem.
In principle, the signal level of the active users can be maintained to a desired level by efficient and fast power control schemes (e.g., a combination of open loop and closed loop methods). However, when a satellite channel with a long propagation delay is involved, realization of fast power control methods are not practical.
In traditional single user CDMA receivers, the received signal is correlated with the bandwidth spreading code of the desired channel, and the interference from other users is considered as additional thermal noise. Data then is detected by comparing the output of the correlator with a threshold. In a single user receiver, no attempt is made to reduce the interference from other users.
A potentially attractive technique for increasing the capacity of direct sequence spread spectrum CDMA has been to employ an efficient and low complexity interference cancellation method which takes advantage of the deterministic nature of interference noise. In this approach, the desired signal is detected by jointly processing the signal of every active user in each receiver.
FIG. 1 is a block diagram of a typical decorrelator detector for a joint CDMA receiver. In such a joint CDMA receiver, the desired signal is detected by processing the output of a bank of correlators, 1-K, implemented in a serial or parallel configuration, each corresponding to one of the active users. This method, while potentially yielding significant improvements in the CDMA channel capacity, requires the availability of bandwidth spreading sequences of the other users at every receive end. Also, it is necessary to obtain a good estimate of every user's instantaneous power level, and to determine the relative time delay/phase of each user, with respect to the desired signal. In principle, interference from other users can be calculated and subtracted from the received signal if all of the information about the transmission channel and the other active users' signals are available at the receiver. This requires tremendous computational capability at receivers. Clearly, not every practical system can meet all of these prerequisites.
The main functions of a typical CDMA Spread Spectrum system can be formulated as follows. For a chip synchronized CDMA system with K active users, let the bandwidth spreading sequence of the ith user be denoted by s.sub.1 (t), t .epsilon. {o,T}, of finite energy, and confined to T seconds. Assume that each bandwidth spreading sequence of period L conveys only one data bit, so that T is also the time duration for transmitting one information bit. Then, in a chip synchronous multiple access channel, the received signal over the time interval O.ltoreq.t.ltoreq.T is ##EQU1## where, d.sub.i =.+-.1 and .alpha..sub.i denote, respectively, the information bit and signal power level of the ith user, and n(t) is additive white Gaussian noise. The above equation represents an ideal CDMA channel model for the received signal of the first information bit (from K users) where perfect chip timing, carrier center frequency, and phase adjustment among users are assumed. Each received chip has a rectangular pulse shape.
Referring again to FIG. 1, the received composite signal, r(t), is correlated by bandwidth spreading sequences s.sub.j (t), 1.ltoreq.j.ltoreq.K.
The output, c.sub.j, of the jth correlator is ##EQU2## is crosscorrelation between sequence s.sub.i (t) and s.sub.j (t), and ##EQU3## is a sample of correlated noise.
In matrix form, equation (1) can be written as EQU C=RA+n
where C.sup.T =[c.sub.1,c.sub.2, . . . , c.sub.k ], A.sup.T =[d.sub.1,d.sub.2, . . . ,d.sub.k ], n.sup.T =[n.sub.1, n.sub.2, . . . , n.sub.k ], and R is a K by K matrix with elements .alpha..sub.i .theta..sub.ji.
In the absence of noise, C=RA, and if R is invertible, estimates for information bits are readily obtained by premultiplying C by the inverse crosscorrelation matrix, W=R.sup.-1. This interference cancellation method, known as the decorrelating detector method, is one of the first techniques devised and published for increasing the capacity of direct sequence CDMA systems. However, it is a suboptimum procedure, because the noise term in equation (1) is correlated. Also, from a practical point of view, its implementation is not straightforward. The inverse of R can be calculated only if the received power levels of all the K active users, .alpha..sub.i, 1.ltoreq.i.ltoreq.K, are known with a fair amount of accuracy. Moreover, the number of active users and the corresponding bandwidth spreading sequences must be known at the receive end. Thus, the complexity of implementation of an optimum interference cancellation method based on the decorrelating detector concept increases exponentially with respect to the number of active users. Additionally, several known interference cancellation techniques are useful and effective only when the interference noise is substantially greater than the thermal noise.